DataCoordinate¶

class lsst.daf.butler.DataCoordinate(*args, **kwds)¶

Bases: lsst.daf.butler.NamedKeyMapping[lsst.daf.butler.Dimension, Optional[Union[str, int]]]

Data ID dictionary.

An immutable data ID dictionary that guarantees that its key-value pairs identify at least all required dimensions in a DimensionGraph.

DataCoordinateSet itself is an ABC, but provides staticmethod factory functions for private concrete implementations that should be sufficient for most purposes. standardize is the most flexible and safe of these; the others (makeEmpty, fromRequiredValues, and fromFullValues) are more specialized and perform little or no checking of inputs.

Notes

Like any data ID class, DataCoordinate behaves like a dictionary, but with some subtleties:

Both Dimension instances and str names thereof may be used as keys in lookup operations, but iteration (and keys) will yield Dimension instances. The names property can be used to obtain the corresponding str names.

Lookups for implied dimensions (those in self.graph.implied) are supported if and only if hasFull returns True, and are never included in iteration or keys. The full property may be used to obtain a mapping whose keys do include implied dimensions.

Equality comparison with other mappings is supported, but it always considers only required dimensions (as well as requiring both operands to identify the same dimensions). This is not quite consistent with the way mappings usually work - normally differing keys imply unequal mappings - but it makes sense in this context because data IDs with the same values for required dimensions but different values for implied dimensions represent a serious problem with the data that DataCoordinate cannot generally recognize on its own, and a data ID that knows implied dimension values should still be able to compare as equal to one that does not. This is of course not the way comparisons between simple dict data IDs work, and hence using a DataCoordinate instance for at least one operand in any data ID comparison is strongly recommended.

Attributes Summary

`full`	Return mapping for all dimensions in `self.graph`.
`graph`	Dimensions identified by this data ID (`DimensionGraph`).
`names`	Names of the required dimensions identified by this data ID.
`records`	Return the records.
`region`	Spatial region associated with this data ID.
`timespan`	Temporal interval associated with this data ID.
`universe`	Universe that defines all known compatible dimensions.

Methods Summary

`byName`()	Return a `Mapping` with names as keys and the `self` values.
`expanded`(records)	Return a `DataCoordinate` that holds the given records.
`fromFullValues`(graph, values)	Construct a `DataCoordinate` from all dimension values.
`fromRequiredValues`(graph, values)	Construct a `DataCoordinate` from required dimension values.
`from_json`(json_str[, universe, registry])	Return new class from JSON string.
`from_simple`(simple[, universe, registry])	Construct a new object from the simplified form.
`get`(k[,d])
`hasFull`()	Whether this data ID contains implied and required values.
`hasRecords`()	Whether this data ID contains records.
`items`()
`keys`()
`makeEmpty`(universe)	Return an empty `DataCoordinate`.
`pack`(name, *[, returnMaxBits])	Pack this data ID into an integer.
`standardize`([mapping, graph, universe, defaults])	Standardize the supplied dataId.
`subset`(graph)	Return a `DataCoordinate` whose graph is a subset of `self.graph`.
`to_json`([minimal])	Convert this class to JSON form.
`to_simple`([minimal])	Convert this class to a simple python type.
`union`(other)	Combine two data IDs.
`values`()

Attributes Documentation

full¶

Return mapping for all dimensions in self.graph.

The mapping includes key-value pairs for all dimensions in self.graph, including implied (NamedKeyMapping).

Accessing this attribute if hasFull returns False is a logic error that may raise an exception of unspecified type either immediately or when implied keys are accessed via the returned mapping, depending on the implementation and whether assertions are enabled.

graph¶

Dimensions identified by this data ID (DimensionGraph).

Note that values are only required to be present for dimensions in self.graph.required; all others may be retrieved (from a Registry) given these.

names¶

Names of the required dimensions identified by this data ID.

They are returned in the same order as keys (collections.abc.Set [ str ]).

records¶

Return the records.

Returns a mapping that contains DimensionRecord objects for all elements identified by this data ID (NamedKeyMapping).

The values of this mapping may be None if and only if there is no record for that element with these dimensions in the database (which means some foreign key field must have a NULL value).

Accessing this attribute if hasRecords returns False is a logic error that may raise an exception of unspecified type either immediately or when the returned mapping is used, depending on the implementation and whether assertions are enabled.

region¶

Spatial region associated with this data ID.

(lsst.sphgeom.Region or None).

This is None if and only if self.graph.spatial is empty.

Accessing this attribute if hasRecords returns False is a logic error that may or may not raise an exception, depending on the implementation and whether assertions are enabled.

timespan¶

Temporal interval associated with this data ID.

(Timespan or None).

This is None if and only if self.graph.timespan is empty.

Accessing this attribute if hasRecords returns False is a logic error that may or may not raise an exception, depending on the implementation and whether assertions are enabled.

universe¶

Universe that defines all known compatible dimensions.

The univers will be compatible with this coordinate (DimensionUniverse).

Methods Documentation

byName() → Dict[str, V_co]¶

Return a Mapping with names as keys and the self values.

Returns

dictionarydict: A dictionary with the same values (and iteration order) as self, with str names as keys. This is always a new object, not a view.

abstract expanded(records: Union[lsst.daf.butler.NamedKeyMapping[lsst.daf.butler.DimensionElement, Optional[lsst.daf.butler.DimensionRecord]], Mapping[str, Optional[lsst.daf.butler.DimensionRecord]]]) → lsst.daf.butler.DataCoordinate¶

Return a DataCoordinate that holds the given records.

Guarantees that hasRecords returns True.

This is a low-level interface with at most assertion-level checking of inputs. Most callers should use Registry.expandDataId instead.

Parameters

recordsMapping [ str, DimensionRecord or None ]: A NamedKeyMapping with DimensionElement keys or a regular Mapping with str (DimensionElement name) keys and DimensionRecord values. Keys must cover all elements in self.graph.elements. Values may be None, but only to reflect actual NULL values in the database, not just records that have not been fetched.

static fromFullValues(graph: lsst.daf.butler.DimensionGraph, values: Tuple[Optional[Union[str, int]], …]) → lsst.daf.butler.DataCoordinate¶

Construct a DataCoordinate from all dimension values.

This is a low-level interface with at most assertion-level checking of inputs. Most callers should use standardize instead.

Parameters

graphDimensionGraph: Dimensions this data ID will identify.
valuestuple [ int or str ]: Tuple of primary key values corresponding to itertools.chain(graph.required, graph.implied), in that order. Note that this is _not_ the same order as graph.dimensions, though these contain the same elements.

Returns

dataIdDataCoordinate: A data ID object that identifies the given dimensions. dataId.hasFull() will return True if and only if graph.implied is empty, and dataId.hasRecords() will never return True.

static fromRequiredValues(graph: lsst.daf.butler.DimensionGraph, values: Tuple[Optional[Union[str, int]], …]) → lsst.daf.butler.DataCoordinate¶

Construct a DataCoordinate from required dimension values.

This is a low-level interface with at most assertion-level checking of inputs. Most callers should use standardize instead.

Parameters

graphDimensionGraph: Dimensions this data ID will identify.
valuestuple [ int or str ]: Tuple of primary key values corresponding to graph.required, in that order.

Returns

dataIdDataCoordinate: A data ID object that identifies the given dimensions. dataId.hasFull() will return True if and only if graph.implied is empty, and dataId.hasRecords() will never return True.

classmethod from_json(json_str: str, universe: Optional[DimensionUniverse] = None, registry: Optional[Registry] = None) → SupportsSimple¶

Return new class from JSON string.

Converts a JSON string created by to_json and return something of the supplied class.

Parameters

json_strstr: Representation of the dimensions in JSON format as created by to_json().
universeDimensionUniverse, optional: The special graph of all known dimensions. Passed directly to from_simple().
registrylsst.daf.butler.Registry, optional: Registry to use to convert simple name of a DatasetType to a full DatasetType. Passed directly to from_simple().

Returns

constructedAny: Newly-constructed object.

classmethod from_simple(simple: Dict[str, Any], universe: Optional[DimensionUniverse] = None, registry: Optional[Registry] = None) → DataCoordinate ¶

Construct a new object from the simplified form.

The data is assumed to be of the form returned from the to_simple method.

Parameters

simpledict of [str, Any]: The dict returned by to_simple().
universeDimensionUniverse: The special graph of all known dimensions.
registrylsst.daf.butler.Registry, optional: Registry from which a universe can be extracted. Can be None if universe is provided explicitly.

Returns

dataIdDataCoordinate: Newly-constructed object.

get(k[, d]) → D[k] if k in D, else d. d defaults to None.¶

abstract hasFull() → bool ¶

Whether this data ID contains implied and required values.

Returns

statebool: If True, __getitem__, get, and __contains__ (but not keys!) will act as though the mapping includes key-value pairs for implied dimensions, and the full property may be used. If False, these operations only include key-value pairs for required dimensions, and accessing full is an error. Always True if there are no implied dimensions.

abstract hasRecords() → bool ¶

Whether this data ID contains records.

These are the records for all of the dimension elements it identifies.

Returns

statebool

If True, the following attributes may be accessed:

records

region

timespan

pack

If False, accessing any of these is considered a logic error.

items() → a set-like object providing a view on D’s items¶

keys() → a set-like object providing a view on D’s keys¶

static makeEmpty(universe: DimensionUniverse) → DataCoordinate ¶

Return an empty DataCoordinate.

It identifies the null set of dimensions.

Parameters

universeDimensionUniverse: Universe to which this null dimension set belongs.

Returns

dataIdDataCoordinate: A data ID object that identifies no dimensions. hasFull and hasRecords are guaranteed to return True, because both full and records are just empty mappings.

pack(name: str, *, returnMaxBits: bool = False) → Union[Tuple[int, int], int]¶

Pack this data ID into an integer.

Parameters

namestr: Name of the DimensionPacker algorithm (as defined in the dimension configuration).
returnMaxBitsbool, optional: If True (False is default), return the maximum number of nonzero bits in the returned integer across all data IDs.

Returns

packedint: Integer ID. This ID is unique only across data IDs that have the same values for the packer’s “fixed” dimensions.
maxBitsint, optional: Maximum number of nonzero bits in packed. Not returned unless returnMaxBits is True.

Notes

Accessing this attribute if hasRecords returns False is a logic error that may or may not raise an exception, depending on the implementation and whether assertions are enabled.

static standardize(mapping: Optional[NameLookupMapping[Dimension, DataIdValue]] = None, *, graph: Optional[DimensionGraph] = None, universe: Optional[DimensionUniverse] = None, defaults: Optional[DataCoordinate] = None, **kwargs: Any) → DataCoordinate ¶

Standardize the supplied dataId.

Adapts an arbitrary mapping and/or additional arguments into a true DataCoordinate, or augment an existing one.

Parameters

mappingMapping, optional: An informal data ID that maps dimensions or dimension names to their primary key values (may also be a true DataCoordinate).
graphDimensionGraph: The dimensions to be identified by the new DataCoordinate. If not provided, will be inferred from the keys of mapping and **kwargs, and universe must be provided unless mapping is already a DataCoordinate.
universeDimensionUniverse: All known dimensions and their relationships; used to expand and validate dependencies when graph is not provided.
defaultsDataCoordinate, optional: Default dimension key-value pairs to use when needed. These are never used to infer graph, and are ignored if a different value is provided for the same key in mapping or **kwargs`.
**kwargs: Additional keyword arguments are treated like additional key-value pairs in mapping.

Returns

coordinateDataCoordinate: A validated DataCoordinate instance.

Raises

TypeError: Raised if the set of optional arguments provided is not supported.
KeyError: Raised if a key-value pair for a required dimension is missing.

abstract subset(graph: lsst.daf.butler.DimensionGraph) → lsst.daf.butler.DataCoordinate¶

Return a DataCoordinate whose graph is a subset of self.graph.

Parameters

graphDimensionGraph: The dimensions identified by the returned DataCoordinate.

Returns

coordinateDataCoordinate: A DataCoordinate instance that identifies only the given dimensions. May be self if graph == self.graph.

Raises

KeyError: Raised if the primary key value for one or more required dimensions is unknown. This may happen if graph.issubset(self.graph) is False, or even if graph.issubset(self.graph) is True, if self.hasFull() is False and graph.required.issubset(self.graph.required) is False. As an example of the latter case, consider trying to go from a data ID with dimensions {instrument, physical_filter, band} to just {instrument, band}; band is implied by physical_filter and hence would have no value in the original data ID if self.hasFull() is False.

Notes

If hasFull and hasRecords return True on self, they will return True (respectively) on the returned DataCoordinate as well. The converse does not hold.

to_json(minimal: bool = False) → str ¶

Convert this class to JSON form.

The class type is not recorded in the JSON so the JSON decoder must know which class is represented.

Parameters

minimalbool, optional: Use minimal serialization. Requires Registry to convert back to a full type.

Returns

jsonstr: The class in JSON string format.

to_simple(minimal: bool = False) → Dict¶

Convert this class to a simple python type.

This is suitable for serialization.

Parameters

minimalbool, optional: Use minimal serialization. Has no effect on for this class.

Returns

as_dictdict: The object converted to a dictionary.

abstract union(other: lsst.daf.butler.DataCoordinate) → lsst.daf.butler.DataCoordinate¶

Combine two data IDs.

Yields a new one that identifies all dimensions that either of them identify.

Parameters

otherDataCoordinate: Data ID to combine with self.

Returns

unionedDataCoordinate: A DataCoordinate instance that satisfies unioned.graph == self.graph.union(other.graph). Will preserve hasFull and hasRecords whenever possible.

Notes

No checking for consistency is performed on values for keys that self and other have in common, and which value is included in the returned data ID is not specified.

values() → an object providing a view on D’s values¶

Navigation

DataCoordinate¶